We present the first direct measurements of NO3 reactivity (or
inverse lifetime, s−1) in the Finnish boreal forest. The data were
obtained during the IBAIRN campaign (Influence of Biosphere-Atmosphere
Interactions on the Reactive Nitrogen budget) which took place in
Hyytiälä, Finland during the summer/autumn transition in
September 2016. The NO3 reactivity was generally very high with a
maximum value of 0.94 s−1 and displayed a strong diel variation with a
campaign-averaged nighttime mean value of 0.11 s−1 compared to a
daytime value of 0.04 s−1. The highest nighttime NO3 reactivity
was accompanied by major depletion of canopy level ozone and was associated
with strong temperature inversions and high levels of monoterpenes. The
daytime reactivity was sufficiently large that reactions of NO3 with
organic trace gases could compete with photolysis and reaction with NO. There
was no significant reduction in the measured NO3 reactivity between
the beginning and end of the campaign, indicating that any seasonal reduction
in canopy emissions of reactive biogenic trace gases was offset by emissions
from the forest floor. Observations of biogenic hydrocarbons (BVOCs) suggested
a dominant role for monoterpenes in determining the NO3 reactivity.
Reactivity not accounted for by in situ measurement of NO and BVOCs was
variable across the diel cycle with, on average, ≈ 30 %
“missing” during nighttime and ≈ 60 % missing during the day.
Measurement of the NO3 reactivity at various heights (8.5 to 25 m)
both above and below the canopy, revealed a strong nighttime, vertical
gradient with maximum values closest to the ground. The gradient disappeared
during the daytime due to efficient vertical mixing.

Biogenic and anthropogenic volatile organic compounds (VOCs) have a
significant impact on air quality and human health and knowledge of their
tropospheric lifetimes, determined by the oxidizing capacity of the lowermost
atmosphere, is a prerequisite to predicting future atmospheric composition
and climate change (Lelieveld et al., 2008). Recent estimates (Guenther et
al., 2012) suggest that about 1000 Tg of biogenic volatile organic compounds
(BVOCs), are emitted annually by vegetation. The boreal forest covers an area
of ≈ 15 million km2 worldwide, which is comparable to
that covered by tropical rainforest (Eerdekens et al., 2009). Forests emit
large amounts of unsaturated hydrocarbons in the form of the terpenoids such
as, isoprene (2-methylbuta-1,3-diene, C5H8), monoterpenes
(C10H16), and sesquiterpenes (C15H24) that have a
significant impact on HOx (HO +HO2) and NOx
(NO +NO2) budgets (Hakola et al., 2003; Tarvainen et al., 2005;
Holzke et al., 2006; Lappalainen et al., 2009) and the formation of secondary
organic particle (Hallquist et al., 2009).

Along with the reaction with O3, BVOCs are oxidized in the
troposphere by reactions with OH and NO3 radicals. OH radical-induced
oxidation mainly takes place during daytime with the NO3 radical
(formed by reaction of O3 with NO2, Reaction R1) accounting
for the major fraction of radical-induced loss of BVOC at nighttime (Wayne et
al., 1991; Atkinson, 2000; Atkinson and Arey, 2003a, b; Brown and Stutz,
2012; Mogensen et al., 2015; Ng et al., 2017; Liebmann et al., 2017). The
rapid photolysis of NO3 by sunlight (Reactions R5, R6) and reaction
with NO (Reaction R2) typically reduces its lifetime to a few seconds during
daytime. At nighttime, reaction of NO3 with NO2 results in
thermal equilibrium between NO3 and N2O5 (Reactions R3,
R4).

Reactions (R1) to (R6) do not represent a reduction of
NOx as no reactive nitrogen species are removed from the gas phase.
However, heterogeneous uptake of N2O5 to particles (R7) and the
reaction of NO3 with BVOCs (forming either HNO3 or organic
nitrates, see below) both result in the transfer of gas-phase NOx to
particulate forms, thus reducing the rate of photochemical O3
formation from NO2 photolysis (Dentener and Crutzen, 1993).

In forested environments at low NOx the lifetime of NO3 with
respect to chemical losses during the temperate months will generally be
driven by the terpenoids (isoprene, monoterpenes, and sesquiterpenes), the
reaction proceeding via addition to the carbon–carbon double bond to form
nitrooxyalkyl peroxy radicals. The peroxy radicals react further (with
HO2, NO, NO2, or NO3) to form multi-functional
peroxides and organic nitrates, which can contribute to the generation and
growth of secondary organic aerosols (Ehn et al., 2014; Fry et al., 2014; Ng
et al., 2017; Liebmann et al., 2017) or be lost by deposition. The main
processes outlining the role of NO3 in removing NOx from the
atmosphere are summarized in Fig. 1. Clearly, the lifetime of NO3
with respect to reaction with BVOCs (the subject of this article)
determines the relative rate of formation of inorganic nitrate via
heterogeneous processes (HNO3) and organic nitrates, which have
different lifetimes with respect to chemical and depositional loss and thus
different efficiencies of NOx removal. It also indirectly determines the
rate of generation of reactive chlorine (in the form of ClNO2)
resulting from the heterogeneous reactions of N2O5 with chloride
containing particles (Osthoff et al., 2008; Thornton et al., 2010; Phillips
et al., 2012, 2016; Ammann et al., 2013).

Reactivity measurements have previously been applied to assess the
overall loss rates of the OH radical in the boreal forest and to test for
closure in its budget (Hens et al., 2014). In forested environments, the
measured reactivity has generally been found to be significantly higher than
that calculated from summing up reactivity due to individual reactive trace
gases, (Sinha et al., 2010; Nölscher et al., 2012, 2016) resulting in an
apparent “missing reactivity”. In a similar vein, O3 flux
measurements in Californian pine forests required monoterpene emissions that
were 10 times higher than measured in order to explain the O3 losses
(Goldstein et al., 2004). These studies argue for the presence of
monoterpenes/sesquiterpenes that are not detected by standard instruments
used to measure BVOCs. Direct measurements of NO3 reactivity were not
available until very recently (Liebmann et al., 2017); hence the reactivity of
NO3 has traditionally been calculated from concentration measurements
by assuming balanced production and loss terms (stationary state, see
Sect. 3.4), or from measurements of the VOCs that contribute to its loss and
the known rate constant for reaction of each VOC with NO3. The first
method may break down when stationary state is not achieved (Brown et al.,
2003). For example, Sobanski et al. (2016b) observed much lower
stationary-state loss rates of NO3 compared to those calculated from
measured VOC mixing ratios in a forested/urban location. It was therefore concluded that
this was mainly the result of sampling from a low-lying residual layer with
VOC emissions that were too close to the sampling point for NO3
concentrations to achieve stationary state. The second method relies on
comprehensive measurement and accurate quantification of all VOCs that react
with NO3, which, in a chemically complex environment such as a
forest, may not always be possible.

In this paper we describe direct, point measurements of NO3
reactivity in ambient air in the boreal forest of southern Finland and
analyse the results using ancillary measurements of NOx, NO3,
O3, and biogenic hydrocarbons as well as meteorological parameters.

The IBAIRN campaign took place in September 2016 in the boreal forest at
Hyytiälä, Finland. September marks the transition from late summer to
autumn at Hyytiälä, with the number of daylight hours at the site
changing from ≈ 14 to 11.5 from the beginning to the end of
September, with the first widespread ground frost occurring close to the end
of the campaign. The relative humidity within the canopy frequently reached
100 % at nighttime, though there was little rainfall during the study period.
By the end of the campaign, the initially green leaves of deciduous trees had
turned brown and fresh needle/leaf litter was accumulating on the forest
floor. The daily profiles of temperature, relative humidity and the
NO3 photolysis rate constant (JNO3) are displayed in
Fig. 2.

Figure 2Overview of measurements during IBAIRN. The grey shaded regions
represent nighttime. The uncertainty in kOTG is given by the green
shaded region. Measurements were obtained from the common inlet at a height of 8.5 m apart from the NO3 photolysis rate (taken from a height of 35 m on an adjacent
tower), wind direction (WD) and wind speed (WS) (both at 16.5 m on the 128 m
tower). A time series of kOTG is given in log scale in the Supplement (Fig. S1).

Figure 2 shows the local wind speed and wind direction at a height of 16 m (close
to the top of the canopy) during the campaign. The wind rose in Fig. 3a indicates that
the prevailing wind was from the north-west and north-east sectors (≈ 60 % of the
time) compared to 28 % from the southern sector, of which only ≈ 8 % came from the south-east. Nonetheless, two isolated plumes from Korkeakoski
were evident as greatly increased values of the NO3 reactivity and
BVOC levels, as discussed later. In general wind speeds at a height of 16 m were
low, favouring a stable boundary layer during nighttime. Wind speed, wind
direction, temperature, precipitation, and relative humidity were monitored at
various heights on the 128 m SMEAR II tower. Details regarding these and
other supporting measurements made at this site can be found elsewhere (Hari
and Kulmala, 2005; Hari et al., 2013). The vegetation at the site consists
mostly of Scots pine (Pinus sylvestris, > 60 %) with
occasional Norway spruce (Picea abies), aspen (Populus sp.)
and birch (Betula sp.). The most common vascular plants are
lingonberry (Vaccinium vitis-idea L.), bilberry (Vaccinium myrtillus L.), wavy hair grass (Deschampsia flexuosa (L.) Trin.)
and heather (Calluna vulgaris (L.) Hull.). The ground is covered
with common mosses as such as Schreber's big red stem moss
(Pleurozium schreberi (Brid.) Mitt.) and a dicranum moss
(Dricanum Hedw. sp.). The canopy height is ≈ 20 m with an
average tree density of 1370 stems (diameter at breast height
> 5 cm) per hectare (Ilvesniemi et al., 2009).

2.2 NO3 reactivity measurement

NO3 reactivity was measured using an instrument that was recently
described in detail by Liebmann et al. (2017). Initially, 40 to 60 pptv of
synthetically generated NO3 radicals (Reaction R1) were mixed with
either zero air (ZA) or ambient air in a cylindrical flow-tube thermostatted
to 21 ∘C. After a reaction time of 10.5 s, the remaining
NO3 was detected by cavity-ring-down spectroscopy (CRDS) at 662 nm.
The measurement cycle was typically 400 s for synthetic air and 1200 s for
ambient air, with intermittent signal zeroing (every ≈ 100 s) by
addition of NO.

The observed loss of NO3 in ambient air compared to ZA was converted
to a reactivity via numerical simulation of a simple reaction scheme
(Liebmann et al., 2017) using measured amounts of NO, NO2, and
O3. The parameter obtained, kOTG, is a loss rate constant
for NO3 from which contributions from NO and NO2 have been
removed, and thus refers to reactive loss to organic trace gases (OTGs) only.
Throughout the article, NO3 reactivity and kOTG are
equivalent terms, with units of s−1. The dynamic range of the instrument
was increased to 0.005–45 s−1 by automated, dynamic dilution of the
air sample, the limit of detection being defined by the stability of the
NO3 source. Online calibration of the reactivity using an NO standard
was performed every 2 h for 10 min. The uncertainty of the measurement was
between 0.005 and 0.158 s−1, depending mainly on dilution accuracy, NO
levels, and the stability of the NO3 source (Liebmann et al., 2017).

The instrument was operated in a laboratory container located in a
gravel-bedded clearing in the forest. Air samples were drawn at a flow rate
of 2900 standard cubic centimetres per minute (sccm) through a 2 µm membrane filter (Pall Teflo) and 4 m of PFA tubing (6.35 mm OD) from the
centre of a high-flow inlet (Ø = 15 cm,
flow = 10 m3 min−1) which sampled at a height of 8 m, 3 m above
the roof of the container and circa 8 m away from the forest edge. Several
instruments sampled from the high-flow and we refer to this as the “common
inlet”. Relative humidity and temperature were monitored in the common inlet
using standard sensors (1st Innovative Sensor Technology, HYT939,
± 1.8 % RH). Vertical profiles of NO3 reactivity (8.5 to
25 m) were measured by attaching 30 m of PFA tubing directly to the
flow tube and raising/lowering the open end (with membrane filter) using a
rope hoist attached to a 30 m tower about 5 m from the container.

2.3 NO, NO2, O3, and NO3 measurements

NO was sampled from the common inlet using a modified commercial
chemiluminescence detector (CLD 790 SR) based on the reaction between NO and
O3 (ECO Physics, Dürnten, Switzerland). The detection limit for
NO was 5 pptv for an integration period of 5 s, the total uncertainty
(2 σ) was 20 % (Li et al., 2015). Ozone was measured by two
instruments based on optical absorption, both sampling from the common inlet.
These were a 2B-Technology, Model 202 and a Thermo Environmental Instruments
Inc., Model 49 both with detection limits of ≈ 1 ppb. The two
instruments had uncertainties (provided by manufacturer) of 5 and 2 %
respectively. Agreement between the two O3 measurements was excellent
(slope = 1.000 ± 0.001, offset of −0.21 ppbv, R2=0.98).
Vertical profiles in O3 (up to 125 m) were made using a TEI 49 C
analyser sampling from inlets at various heights on a tower located 130 m
north–north-west of the measurement container. NO2 and
NO3 were measured from the common inlet using a multi-channel,
thermal dissociation-cavity ring down spectrometer (TD-CRDS) recently
described in detail by (Sobanski et al., 2016a). NO3 radicals were
detected at 662 nm with a detection limit of 1.3 pptv (1 min averaging)
and an uncertainty of 25 %. NO2 was detected at 405 nm with an
uncertainty of 6 % and a detection limit of 60 pptv (1 min averaging).

2.4 VOC measurements

Three different instruments were used to monitor VOCs, including (1) a gas
chromatograph equipped with an atomic emission detector (GC-AED) which
sampled from the common inlet; (2) a thermal desorption gas chromatograph
with mass spectrometric detection (GC-MS) sampling about 1.5 m above the
ground and ≈ 10 m away from the reactivity measurements; and
(3) and a proton transfer reaction time of flight mass spectrometer
(PTR-TOF-MS) located about 170 m away in dense forest and sampling at a
height of ≈ 2.5 m above the ground.

2.4.1 GC-AED

The GC-AED consisted of a cryogenic pre-concentrator coupled to an Agilent
7890B GC and an atomic emission detector (JAS AEDIII, Moers, Germany). The
GC-AED sampled air through a 15 m long, 1/2′′ (1.27 cm) outer diameter
PFA Teflon tube (flow rate = 20 L min−1, transmission time 3.3 s)
which was heated to ≈ 10 ∘C above ambient. The instrument
was calibrated in situ with an 84-component gravimetrically prepared
gas-phase calibration reference standard with a stated accuracy of better
than ±5 %
(Apel-Riemer Environmental, Inc., Florida, USA). The average total
uncertainty of the species measured from repeated calibration standard
measurements combined with the flow measurements and calibration standard
uncertainty was calculated to be 14 %. α-pinene, Δ-3-carene, β-pinene, camphene, and d-limonene were all calibrated
individually. Detection limits for the monoterpene species were 1.0, 0.9,
0.4, 0.5, and 0.3 pptv respectively. As this is the first deployment of this
instrument, more details are provided in the Supplement: a full description
will be the subject of an upcoming publication.

2.4.2 GC-MS

The GC-MS was located in a container in a gravel-bedded clearing about 4 m
from the edge of the forest and ≈ 30 m away from the common inlet.
Air samples were taken every other hour (30 min sampling time) at a height of
1.5 m by drawing air at 1 L min−1 through a 1 m long fluorinated
ethylene propylene (FEP) inlet (inner diameter 1/8 inch). Ozone was removed via a heated
(120 ∘C) stainless steel tube (Hellén et al., 2012). VOCs were
collected from a 40 mL min−1 subsample flow into the cold trap (Tenax
TA/ Carbopack B) of the thermal desorption unit (TurboMatrix, 650,
Perkin-Elmer) connected to a gas chromatograph (Clarus 680, Perkin-Elmer)
with HP-5 column (60 m, inner diameter 0.25 mm, film
thickness 1 µm) coupled to a mass spectrometer (Clarus SQ 8 T,
Perkin-Elmer). The instrument was used for measurements of isoprene,
monoterpenes, and aromatic hydrocarbons and was calibrated for all individual
compounds using liquid standards in methanol solutions, which were injected
into the Tenax TA/Carbopack B adsorbent tubes and analysed with the same
method as the air samples. Detection limits for monoterpenes (α-pinene, camphene, β-pinene, 3Δ-carene, myrcene, p-cymene,
limonene, 1,8-cineol, and terpinolene) were 0.2–1.2 pptv and for β-caryophyllene 0.8 pptv. The average total uncertainty (10 % for all
monoterpenes and β-caryophyllene) was calculated from the
reproducibility of the calibrations,
uncertainty of the standard preparation and the uncertainty in the sampling
flow.

2.4.3 PTR-TOF-MS

The PTR-TOF-MS (PTR-TOF 8000, Ionicon Analytic GmbH) measures whole VOC
spectra in real time (Jordan et al., 2009; Graus et al., 2010) with mass
resolution of 4500 (full width at half maximum). The instrument was located
in the main cottage, approximately 170 m away from the common inlet. Ambient
air was sampled from 2.5 m above the ground, using a 3.5 m long (4 mm
inner diameter) PTFE sampling air at 20 L min−1. A subsample flow of
1 L min−1 was passed via 10 cm of PTFE tubing (1.6 mm inner diameter), by way of a
three-way valve and 15 cm of PEEK tubing (1 mm inner diameter) to the PTR-TOF-MS. The
raw data was collected with 10 s resolution. The instrument measured total
monoterpenes at m/z=137 and isoprene at m/z=69, which were calibrated
with a gas standard (Apel Riemer Environmental Inc., USA) containing isoprene
and α-pinene. The calibration set up and routine are described in
detail in Schallhart et al. (2016). The campaign average limit of detection
(LOD, 3σ, 10 min time resolution) was 5.5 and 3.2 pptv for isoprene
and monoterpenes respectively.

NOx mixing ratios were generally low during the campaign with NO2
between 0.1 to 1.84 ppbv with a campaign average of 0.32 ppbv showing
little variation across the diel cycle. The mean daytime NO mixing ratio was
43 pptv while nighttime NO was close to or below the limit of detection
(≈ 5 pptv) and its contribution to the loss of NO3 was
generally insignificant (see below). Ozone mixing ratios showed large
day/night differences with daily maxima between 30 and 40 ppbv, whilst
nighttime values were as low as 5–10 ppbv. Possible reasons for the large
changes in O3 across the diel cycle are addressed in Sect. 3.1.

3.1 NO3 reactivity and nighttime loss of O3

NO3 reactivity was measured from 5 September 12:00 UTC to 22
September 05:30 UTC; the 1 min averaged time series of kOTG is
displayed in Fig. 2. The overall uncertainty in kOTG is given by
the green, shaded region. NO3 photolysis and reaction with NO result
in concentrations that are generally below the detection limit of modern
instruments during daytime and steady-state calculations of NO3
reactivity are lower limit estimates. In contrast, our direct approach allows
us to derive and analyse daytime values of kOTG as long as NOx
measurements are available (see above). Figure 2 indicates that, in general,
the NO3 reactivity was highest at nighttime; the maximum observed
values in kOTG was 0.94 s−1, (at 21:00 UTC on 9 September)
implying a lifetime of just 1 s and a very reactive air mass at this time.
The mean nighttime value of kOTG was ≈ a factor ten
lower at 0.11 s−1, the daytime mean even lower at 0.04 s−1.
Broadly speaking, the nighttime NO3 lifetimes during IBAIRN were very
short (≈ 10 s on average) compared to previous indirect, ground
level measurements in other locations where several groups have reported
lifetimes of hundreds to thousands of seconds (Heintz et al., 1996; Allan et
al., 1999; Geyer et al., 2001; Aldener et al., 2006; Ambrose et al., 2007;
Brown et al., 2009; Crowley et al., 2010, 2011; Sobanski et al., 2016b). Our
short NO3 lifetimes are, however, compatible with the very low
NO3 mixing ratios observed in forested regions with high rates of
emission of biogenic trace gases (Gölz et al., 2001; Rinne et al., 2012;
Ayres et al., 2015).

Figure 3b illustrates the dependence of kOTG on wind direction.
Air masses from the northern sector were generally associated with lower
reactivity (< 0.2 s−1) whereas all incidents of reactivity
larger than 0.3 s−1 were associated with air masses from the SE sector.
Enhanced reactivity from the south-east may be caused by emissions from the sawmill
at Korkeakoski (Eerdekens et al., 2009), or a local woodshed storing freshly
cut timber about 100 m away from the containers. This may have been
compounded by the lower than average wind speeds associated with air masses
from the south-east, which reduced the rate of exchange between the nocturnal
boundary layer and above canopy air, effectively trapping ground-level
emissions into a shallow boundary layer. Emissions from the sawmill reaching
the site on the night of the 9–10 September provided a useful test of our
method at high reactivity.

In order to examine the difference in daytime and nighttime NO3
reactivity and also explain the large nighttime variability in
kOTG we categorize the nights into three broad types: (1) nights
with strong temperature inversion where the NO3 reactivity was
greatly increased compared to the previous or following day, (2) nights
without temperature inversion with comparable (usually low) daytime and
nighttime NO3 reactivity, and (3) events with unusually high
NO3 reactivity. Figure 4 shows an expanded view of kOTG
over a five day/night period (5–10 September) in which all three types are
represented. It also plots the temperature at different heights as well as
the RH and O3 measured in the common inlet at 8.5 m height.

Figure 4Expanded view of five campaign days illustrating the three types
(1–3) of night encountered. Type 1 has a strong vertical gradient in
temperature (T) and significant O3 loss with relative humidity (RH) at
100 %. Type 2 (no temperature inversion), has little or no O3 loss.
Type 3 is influenced by emissions from the Korkeakoski sawmill.

3.1.1 Type 1 and type 2 nights

Within this 5-day period, the nights on which the reactivity was high
relative to the day (type 1) are the 5–6 and 8–9. These nights are
characterized by large depletion in O3, a significant temperature
inversion of 5–7 ∘C between heights of 8 and 128 m, and a relative
humidity of 100 % directly after sunset. In contrast, two interspersed
nights with comparable reactivity to daytime values (6–7, 7–8, type 2)
display much weaker (if any) nighttime loss of O3 compared to levels
during the previous day, no significant temperature inversion and a relative
humidity less than 100 %. The observations within this period can be
extended to all campaign days. Figure 5 presents the diel cycle of
kOTG and O3 mixing ratios separated into nights of type 1
(with temperature inversion) and type 2 (no temperature inversion). The
shaded regions represent the variability of the measured values. During 24 h
periods in which the night was characterized by strong temperature inversion
(panel (a) in Fig. 5), the O3 mixing ratios display a large
diel variation, with a maximum of 35 ppbv at about 13:00 UTC dropping
rapidly to a minimum of ≈ 13 ppb between midnight and sunrise at
around 05:00 UTC. O3 depletion due to its slow reaction with
NO2 (present at maximum 2 ppbv at night) does not contribute
significantly to its loss even if all resultant NO3 reacts to form
organic nitrates rather than to form N2O5 and re-release NOx.

The O3 mixing ratio shows an inverse diel profile to the NO3
reactivity raising the possibility that the rapid loss of ozone is linked to
high NO3 reactivity; the large values of kOTG and rapid
O3 depletion observed on nights with a significant temperature
inversion are clear indicators that nighttime boundary layer dynamics plays a
key role in controlling both the NO3 reactivity and O3 loss.
A strong nocturnal temperature inversion will weaken the mixing within or
ventilation of the lowermost boundary layer causing a build-up of reactive,
biogenic emissions in the lower layer, and also prevent
down-mixing of drier, O3-rich air leading to the apparent higher loss
rate of O3 and higher relative humidity. The strong anti-correlation
between kOTG and O3 may also provide a clue to the origin
of the O3 loss. Whilst the generally high NO3 reactivity can,
to a large extent, be explained by the presence of reactive trace gases (see
Sect. 3.2), the precipitous loss of O3 on several nights when
kOTG was high (see Figs. 2 and 4) may have components of both dry
deposition and gas-phase reactions.

The campaign averaged, diel variation of ozone at different heights (4 to
125 m) as measured at the SMEAR II tower (Fig. S2 of the Supplement)
indicate that the most rapid losses of ozone are at the lowest heights,
around and below the canopy. Ozone is generally removed from the lower
troposphere by both stomatal and non-stomatal deposition, the latter
involving loss to surfaces and soil. The reactive, gas-phase loss mechanisms
of O3 and NO3 are in some ways similar, as both react with NO
to form NO2, or with unsaturated VOCs by addition to the double bond.
We estimated the loss rate constant for O3 due to its reaction with
terpenes using approximate ambient mixing ratios from 20:00 to 00:00 UTC on
the 20 September for d-limonene (20 pptv), α-pinene (400 pptv),
Δ-carene (100 pptv), and β-pinene (100 pptv) and using
literature rate constants for the O3+ terpene reactions. The
calculated O3 loss (only 2 % from 20:00 to 00:00 UTC) is clearly
insufficient to explain the IBAIRN observations. We also note that the
presence of high concentrations of terpenes when the site was impacted by the
Korkeakoski sawmill resulted in the largest NO3 reactivity observed,
but did not lead to large O3 losses (Fig. 4). As leaf stomata are
closed during nighttime, the decrease in O3 can be attributed either
to non-stomatal deposition or chemical sinks due to reaction with reactive
biogenic trace gases (not the measured monoterpenes) and NO. Previous studies
of O3 loss in forests have highlighted the potential role of
unidentified, reactive organic compounds (Kurpius and Goldstein, 2003;
Goldstein et al., 2004; Holzinger et al., 2006; Rannik et al., 2012). In
contrast to monoterpenes, which react only slowly with O3 (rate
constants are ≈ 10−16–10−17 cm3 molecule−1 s−1),
sesquiterpenes can react rapidly; for example, for β-caryophyllene the
rate coefficient is kO3=1.2×10-14 cm3 molecule−1 s−1 (IUPAC, 2017). The
presence of sesquiterpenes would therefore provide an explanation for the
observations of high NO3 reactivity and rapid O3 loss. We
examine the potential role of sesquiterpenes in more detail in Sect. 3.2
where the contribution of measured terpenoids to NO3 reactivity is
discussed. We also note that recent modelling studies using Hyytiälä
data (Chen et al., 2018; Zhou et al., 2017) conform that O3 depletion
events are associated with the formation of a shallow boundary layer and high
relative humidity. Zhou et al. (2017) conclude that chemical reaction plays
only a minor role in ozone loss processes during the night, which was
suggested to be dominated by deposition to wet surfaces at relative humidity
> 70 %, which is in accord with laboratory investigations
(Sun et al., 2016).

3.1.2 Type 3 nights

The period between the evening and midnight on the 9 September is an example
of a type 3 night, with extremely high NO3 reactivity, which was not
accompanied by significant O3 depletion, temperature inversion or a
RH of 100 %. The apparently anomalously high reactivity on this night can
be traced back to a change in wind direction, which swept from easterly to
southerly during this period, bringing air that was impacted by monoterpene
emissions from the sawmill in Korkeakoski. High mixing ratios of terpenoids
in air masses that have passed over the sawmill have been documented
frequently (Eerdekens et al., 2009; Sinha et al., 2010; Liao et al., 2011;
Hakola et al., 2012; Nölscher et al., 2012). Other occurrences of sawmill
contaminated air during IBAIRN were on the 10 September from 18:40 to
19:00 UTC and on the 14 September from 06:30 to 08:00 UTC, HYSPLIT
back-trajectories (GDAS global, 0.5∘), indicating that the air mass
passed over Korkeakoski ≈ 0.5 h prior to reaching the SMEAR II
site.

In this section we compare kOTG with NO3 reactivity
calculated from ambient VOC mixing ratios. During IBAIRN, three instruments
(GC-MS, GC-AED, and PTR-TOF) measuring VOCs were deployed (see Sect. 2.5 for
details). As the PTR-TOF reports only a summed mixing ratio of all
monoterpenes, ΣMT(PTR-TOF), we first generated an equivalent
parameter for the two GCs, ΣMT(GC-MS) and ΣMT(GC-AED). For
the GC-MS, α-pinene, β-pinene, Δ-carene, d-limonene,
camphene, myrcene, and terpinolene were considered whereas for the GC-AED,
α-pinene, β-pinene, Δ-carene, camphene, and
d-limonene were taken into account. The ΣMT data are displayed as a
time series in Fig. 6, which indicates large differences between the three
measurements as highlighted in Fig. S3 of the Supplement). While the ΣMT(GC-AED) and ΣMT(PTR-TOF) data are in reasonable agreement,
especially when mixing ratios were large, the values reported by the GC-MS
are consistently and significantly lower (factor 2 to > 10)
than those of the others instruments. The time dependent variability in the
differences in ΣMT reported by the GC-MS, GC-AED, and PTR-TOF is a
strong indication that the cause is most likely related to instrument
location and inhomogeneity in terpene emissions within the forest. Whilst the
GC-AED sampled from the common inlet at a height of 8.5 m, which was also used
for the NO3 reactivity measurements, the inlet of the GC-MS was
≈ 10 m away and sampled 1.5 m above the gravel covered
clearing, very close to the side of the container which housed the
instrument. The PTR-TOF-MS was located roughly 170 m away in a wooden
cottage directly surrounded by dense forest and sampled close to the forest
floor at a height of ≈ 1.5 m. With very low within-canopy
wind speeds, especially during nighttime, both horizontal as well as vertical
mixing in the forest and in the clearing are weak so that each
VOC measurement may, to some extent, reflect the mixture and total amount of
BVOCs that are very locally emitted. This aspect was examined by comparing
individual monoterpenes measured by the GC-MS and the GC-AED. The results,
presented as correlation plots for 4 monoterpenes in Fig. S4 of the
Supplement, show that the monoterpene ratios measured by the two instruments
(GC-AED/GC-MS), were variable with values of 1.69 ± 0.06 for α-pinene, 2.51 ± 0.09 for β-pinene, 4.29 ± 0.21 for
Δ-carene, and 0.45 ± 0.03 for d-limonene. A similar picture
emerges for isoprene, for which the GC-AED measured mixing ratios that were a
factor 2–5 larger than measured by the GC-MS. The variable relative
concentrations of monoterpenes reported by each instrument is further
evidence of the inhomogeneity of emissions within the forest and also the
influence of different tree chemotypes within single tree-families in
Hyytiälä, which can exhibit vastly different emission rates of
various monoterpenes (Bäck et al., 2012; Yassaa et al., 2012).

Figure 6Time series of total monoterpenes from
GC-AED (black), GC-MS (red), and PTR-TOF-MS (blue). The data are reproduced
as histograms in Fig. S3 of the Supplement.

For the purpose of comparing our point measurements of kOTG with
NO3 reactivity calculated from BVOC measurements, we restricted our
analysis to the data set obtained by the GC-AED, which sampled from the same
inlet. Nonetheless, when comparing measured NO3 mixing ratios with
those calculated from NO3 reactivity and its production term (see
Sect. 3.4) we use both GC-based datasets.

The loss rate constant, kOTG, represents chemical reactions of
[NO3] with all organic trace gases present, and can be compared to the
loss rate constant (kGC-AED) obtained from the concentrations of
VOCs in the same air mass as measured by the GC-AED, and the rate coefficient
for reaction with NO3:

(1)kGC-AED=∑kiCi,

A difference in the values of kOTG and kGC-AED is
defined as missing reactivity (s−1):

(2)missing reactivity=kOTG-kGC-AED;

where [Ci] is the measured VOC concentration and ki the
corresponding rate constant. The rate constants used in these calculations of
kGC-AED were taken from the IUPAC evaluation (IUPAC, 2017).
Figure 7 (lower panel) shows the concentrations of the monoterpenes as
measured by the GC-AED. The dominant monoterpene was α-pinene
followed by Δ-carene, β-pinene, d-limonene, and camphene.
The GC-AED also detected myrcene and
linalool and
some other terpenes but the very low mixing ratios meant that none of them
contributed significantly to NO3 loss.

In Fig. 7 (upper panel) we overlay the time series of kOTG and
kGC-AED. For clarity of presentation we have omitted to plot the
overall uncertainty of each measurement, which was calculated as described
previously (Liebmann et al., 2017) and is plotted in Fig. S6 of the
Supplement. The correlation between kOTG and kGC-AED is
displayed as Fig. S7 of the Supplement and indicates, on average, that
measured organics accounted for ≈ 70 % of the total NO3
reactivity.

The uncertainty associated with kGC-AED was calculated by
propagating uncertainty in the mixing ratios of the individual terpenes
(14 %, mainly resulting from uncertainty in the calibration standard and the calibration
reproducibility) and assuming 15 % uncertainty in the rate coefficients for
reactions of NO3 with each terpene. The values of kOTG
and kGC-AED do not agree within their combined uncertainties,
indicating that the missing reactivity calculated in Eq. (3) is statistically
significant. Figure 8 plots the time series of the fractional contribution to
kGC-AED made by monoterpenes detected by the GC-AED. The GC-AED
derived NO3 reactivity is dominated by α-pinene and Δ-carene and to a lesser extent d-limonene, with minor contributions from
β-pinene, camphene, and isoprene.

Figure 8Fractional contribution of individual monoterpenes (measured by the
GC-AED) to kGC-AED indicating the dominant role of α-pinene
and Δ-carene.

In Fig. 9 we plot the diel profiles of
kOTG and kGC-AED
(s−1) averaged for the whole campaign. To do this, we interpolated the
values of kOTG, obtained with 60 s time resolution averaged to
900 s data onto the low-time resolution (≈ 60 min) GC-AED
dataset. In the lower panels of Fig. 9 we plot two separate diel profiles,
separating the data into nights with (middle panel) and without (lower panel)
strong temperature inversion. The missing reactivity (in s−1) across the
entire diel profile is between ≈ 0.02 and 0.07, the larger value
encountered during nighttime. In contrast, the fraction of missing reactivity
within the campaign averaged diel cycle was observed during daytime (≈ 60 %), with only 30 % missing at nighttime. The lowermost panel of
Fig. 9 highlights the fact that kOTG was lower during campaign
day/night periods with no temperature inversion and shows that it is roughly
constant across the diel cycle. Likewise, the diel cycle in the reactivity
attributed to the monoterpenes is also constant, with a missing reactivity of
between 0.02 and 0.04 s−1. A different picture emerges for the diel
cycle considering only the days/nights with strong temperature inversion. On
average, we see a much higher nighttime reactivity, which is tracked in its
diel profile by that calculated from the measured monoterpenes. In this case,
the missing reactivity is generally higher and more variable, with values
between 0 and 0.1 s−1.

Figure 9(a) Campaign averaged diel cycle of NO3 reactivity
(kOTG) and the reactivity calculated from the monoterpenes reported
by the GC-AED. The error bars represent the overall uncertainty in each
parameter and not variability. Panels (b) and (c) show data
from type 1 nights (significant nocturnal temperature inversion) and type 2
nights (weak or no nocturnal temperature inversion)
respectively.

Although statistically significant, the fraction of reactivity missing is
much smaller than that reported for OH at this site (Nölscher et al.,
2012) whereby up to 90 % of the observed reactivity was unaccounted for
when the forest was under stress due to high temperatures. For OH, the
fractional missing reactivity was also greatest when the overall reactivity
was high, which is in contrast with the situation for NO3 where
missing reactivity was highest when the overall reactivity was low (i.e.
during daytime). The OH radical reacts with most hydrocarbons and many
inorganic trace gases and may be considered unselective in its reactivity,
whereas NO3 is a more specific oxidant of VOCs, its reactions in the
forest dominated by addition to unsaturated VOCs or reaction with NO.

As the nighttime mixing ratios of NO were low (< 5 pptv apart
from the night 20–21 September when a mixing ratio of ≈ 25 pptv
was measured), its contribution to the overall nighttime loss of NO3
was insignificant. Figure S8 of the Supplement indicates that, averaged over
the entire campaign, NO accounted for less than 2 % of the reactive loss of
NO3 at night. A different picture emerges for daytime, for which the
campaign averaged contribution of NO to the overall chemical reactivity of
NO3 peaked at 40 % at about 10:00 UTC. However, even during
daytime, the average missing reactivity of 0.025 s−1 (Fig. 9) would
require an extra 40 pptv of NO to account for it, which is clearly not
within the total uncertainty of the NO measurement.

A more plausible explanation for the missing NO3 reactivity is
incomplete detection of all reactive BVOCs by the GC-AED, which does not
report mixing ratios of some hydrocarbons such as
2-methyl-3-buten-2-ol, p-cymene, and 1,8 cineol, which the GC-MS showed to be
present. The GC-MS mixing ratios of these species (which react slowly with
NO3) were however too low for them to contribute significantly, even
taking into account the potentially larger concentrations at the common
inlet.

We also consider the potential role of sesquiterpenes. Mixing ratios of
β-caryophyllene reported by the GC-MS were generally low, with a
maximum value of 25 pptv. However, the rate coefficient reported (Shu and
Atkinson, 1995) for the reaction of NO3 with β-caryophyllene
is large (1.9×10-11 cm3 molecule−1 s−1) and
sesquiterpenes at levels of 10 s of pptv can contribute significantly to
NO3 loss rates. Like monoterpenes, the emissions of sesquiterpenes
are driven by temperature, with tree emissions most important during the
hottest months (Duhl et al., 2008). Whilst previous studies at this site
(Hakola et al., 2006) found no correlation between the β-caryophyllene
and monoterpene emissions of an enclosed Scots pine branch, we find that
β-caryophyllene mixing ratios (reported by the GC-MS) are correlated
with those of several monoterpenes measured by the same instrument. This is
illustrated in Fig. S5 of the Supplement which indicates β-caryophyllene/monoterpene ratios (α-pinene β-pinene and
Δ-carene) of 0.061 ± 0.002 (R2 0.86), 0.294 ± 0.011
(R2 0.86), and 0.181 ± 0.007 (R2 0.84), respectively. As
the monoterpenes and sesquiterpenes have very different lifetimes with
respect to chemical loss, we have excluded the sawmill impacted data (red
data point) as sesquiterpenes are unlikely to survive the ≈ 0.5 h.
transport time from Korkeakoski due to their rapid reaction with O3.
The high levels of β-caryophyllene measured may indicate that the
source during IBAIRN is unlikely to be Scots pine, the emissions from which
are strongly temperature dependent during the summer months but low and
independent of temperature in September (Hakola et al., 2006).

A rough estimate of the β-caryophyllene mixing ratio at the common
inlet may be obtained from the GC-AED measurement of α-pinene and the
α-pinene/β-caryophyllene ratios measured by the GC-MS (see
above). The resulting β-caryophyllene mixing ratios lie between 10 and
60 pptv, which, based on a rate constant of 1.9×10-11 cm3 molecule−1 s−1, results in a contribution to
NO3 reactivity of up to 0.03 s−1. As β-caryophyllene
emissions from pine tree needles reveals a strong temperature dependence
(Hakola et al., 2006) it seems unlikely that this is an important source of
β-caryophyllene during the relatively cold September nights of the
IBAIRN campaign and its emissions from other sources, especially those at
ground level including soil may be more important (Insam and Seewald, 2010;
Penuelas et al., 2014).

In summary, the BVOC measurements indicate that NO3 reactivity in
this boreal environment is dominated by reaction with monoterpenes with, on
average, 70 % of the reactivity during nighttime and 40 % of the
reactivity during daytime explained by α- and β-pinene,
Δ-carene, limonene, and camphene. Unidentified
monoterpenes/sesquiterpenes are likely to account for a significant fraction
of the VOC-derived missing reactivity.

Previous estimates of NO3 reactivity (often reported as its inverse
lifetime) have relied on NO3 concentration measurements and the
assumption that the production and loss of NO3 are in stationary state.
By combining kOTG and other loss processes such as photolysis and
reaction with NO with the NO3 production term, we can also calculate
the NO3 concentration:

NO3ss=NO3productionrateNO3lossrate(3)=O3NO2k1kOTG+JNO3+NOk2,

where k1 is the rate constant
(cm3 molecule−1 s−1) for reaction of NO2 with
O3 and k2 is the rate constant
(cm3 molecule−1 s−1) for the reaction of NO3 with NO
and JNO3 is its photolysis rate constant (s−1).
JNO3 was calculated from actinic flux measurements (spectral
radiometer, Metcon GmbH; Meusel et al., 2016) and NO3 cross
sections/quantum yields from an evaluation (Burkholder et al., 2016). This
expression does not consider indirect loss of NO3 via heterogeneous
loss processes of N2O5, which, given the high levels of BVOC
(short NO3 lifetimes) and low aerosol surface area, cannot contribute
significantly.

Figure 10 plots the time series of measured NO3 mixing ratios (1 min
averages, blue lines) for the entire campaign, which indicates that
NO3 was always below the detection limit of 1.3 pptv, which is
defined by variation in the zero-signal rather than random noise (Sobanski et
al., 2016a). The fact that the measured NO3 mixing ratios are
slightly negative (by ≈ 0.2 pptv) is due to a few percent
NO2 contamination of the NO sample used to zero the NO3
signal. We also plot the time series (black line) of the stationary state
NO3 mixing ratios, [NO3]ss, calculated according
to (Eq. 3). The low NOx levels and moderate O3 levels combine to
result in a weak production rate for NO3 of less than
0.03 pptv s−1 for the entire campaign resulting in predicted levels of
[NO3]ss of less than 0.2 pptv. On two nights, higher
mixing ratios close to 1 pptv (nights of 6–7 and 10–11) are predicted, a
result of elevated production rates due to higher NO2 levels.

Figure 10Stationary state NO3 mixing ratios calculated from the
production term (k1[NO2][O3]) and using either
kOTG+k2[NO] +JNO3 (b, black
line), kGC-MS+k2[NO] +JNO3
(b, red line), or
kGC-MS+k2[NO] +JNO3 (b, blue
line)as loss terms. For comparison, the measured NO3 mixing
ratios are also plotted (a, blue line) as well as the 1.3 pptv
limit of detection (horizontal red line).

The advantages of directly measured kOTG rather than reactivity
calculations based on measurements of reactive trace gases is illustrated by
plotting the predicted NO3 levels based on the reactive hydrocarbons
reported by the GC-AED and GC-MS, i.e. use of kGC-MS and
kGC-AED rather than kOTG. Use of the GC-MS data, which
reported the lowest levels of biogenic hydrocarbons, would lead to the
prediction of measurable amounts (up to 4 pptv) of NO3 on several
nights, contradicting our NO3 measurements and previous reports
(Rinne et al., 2012) of very low NO3 levels at this site.

3.4 Vertical gradient in NO3 reactivity

Both column and point measurements of tropospheric NO3 indicate a
strong vertical gradient in its mixing ratio with significantly elevated
levels aloft (Aliwell and Jones, 1998; Allan et al., 2002; von Friedeburg et
al., 2002; Stutz et al., 2004; Brown et al., 2007a, b; Brown and Stutz,
2012). The NO3 gradient is the result of lower production rates close
to the ground, where O3 levels are depleted due to deposition and
also lower loss rates aloft as the concentration of reactive traces gases
from ground level emissions decreases with altitude. High resolution data
(Brown et al., 2007b) indicate that the largest gradient in NO3
concentration is often found in the lowermost 50 m. Nighttime monoterpene
mixing ratios in forested, boreal regions have been found to display a
vertical gradient, with highest mixing ratios at lower levels (Holzinger et
al., 2005; Rinne et al., 2005; Eerdekens et al., 2009). This is a result of
direct emissions, such as monoterpenes from the trees at canopy level; and
emissions of monoterpenes and sesquiterpenes from rotting leaf litter into a
shallow, stratified boundary layer, suggesting that reactive species close to
the ground will dominate in controlling the NO3 lifetime and thus
mixing ratio (Aaltonen et al., 2011). We explored this by measuring kOTG at various heights above ground, including measurements
from a few metres below the canopy, to a few metres above the tree tops.
Altogether we recorded 14 vertical profiles on the 18 September 2016, five
obtained during the daytime (10:15–05:15 UTC) and nine obtained at nighttime
(16:00–24:00 UTC).

Figure 11 displays the averaged nighttime and daytime values of
kOTG recorded at 8.5, 12.0, 17.0, 22.0, and 27.0 m. The total time
to take a single profile was < 15 mins. During the day (black
data points), we find no significant vertical gradient in NO3
reactivity, which was roughly constant at ≈ 0.03 s−1. In
contrast, the average nighttime vertical profile (red data points) reveals a
strong gradient in kOTG with the highest values slightly below
canopy height (8.5 to 12.5 m) with a rapid decrease above. At 20 m and
above, daytime and nighttime values of kOTG were comparable.
These observations are qualitatively consistent with gradients in monoterpene
mixing ratios in this forest (Rinne et al., 2005) and with the conclusion of
Mogensen et al. (2015), who considered NO3 reactions with monoterpenes
and sesquiterpenes emitted from Scots pines at canopy height for the
exceptionally warm summer of 2010. The modelled, nighttime vertical gradient
in NO3 described by Mogensen et al. (2015) displays a maximum at
12 m but differs from the measured gradient from IBAIRN in that lower reactivity
was modelled at the lowest heights, which may be expected as the model
considered only emissions of reactive BVOCs from trees and not from ground
sources. In contrast to the vertical gradient measured during IBAIRN, the
modelled NO3 reactivity showed highest values during daytime,
coincident with the maximum NO mixing ratio (Mogensen et al., 2015) but was generally lower
than our measured values. Mogensen et al. (2015)
indicate that the model is likely to underestimate the NO3 reactivity
due to compounds that cannot be measured by GC-MS as well as by the unknown
products of their oxidation.

Figure 11Vertical profiles of NO3 reactivity (kOTG) on
17–18 September 2016. The data represent the average of five profiles during
the day and nine profiles during the night.

The increase in kOTG below the canopy may be caused by ground
level emissions of reactive trace gases from tree and plant debris or other
flora (mosses, lichens) at forest-floor level. α-pinene and Δ3-carene, emissions from ground level may vary with litter quality and
quantity, soil microbial activity and the physiological stages of plants (Warneke
et al., 1999; Insam and Seewald, 2010; Aaltonen et al., 2011; Penuelas et
al., 2014). Previous work in the tropical forest has indicated that
sesquiterpenes concentrations can peak at ground level rather than within the
canopy (Jardine et al., 2011), although the applicability of this result to the
boreal forest is unclear.

We conclude that high rates of emission of reactive gases into the
stratified nocturnal boundary layer along with ventilation and dilution
above canopy height result in strong nocturnal gradients in NO3
reactivity. During the daytime, efficient turbulent mixing removes the
gradient. We did not obtain a vertical profile of kOTG on a night when
the temperature inversion was absent, but expect it would be significantly
weaker, as is the gradient in O3 on such nights.

Figure 12The fraction, f, of the total NO3 loss with organic trace
gases as a time series (a) and as a campaign averaged, diel cycle
(b) where f=kOTG/(kOTG+JNO3+kNO).

3.5 High NO3 reactivity and its contribution to NOx loss

The high reactivity of NO3 towards organic trace gases in the boreal
environment means that other loss processes, including formation of
N2O5 or reaction with NO are suppressed. To a first approximation
we can assume that, at nighttime, in the absence of NO and sunlight, each
NO3 radical formed in the reaction of NO2 with O3 will react
with a biogenic hydrocarbon, resulting in formation of an organic nitrate at
a yield of between 20 and 100 %, depending on the identity of the organic
reactant (Ng et al., 2017). The large values for kOTG obtained during
the day mean that a significant fraction of the NO3 formed can be
converted to organic nitrates rather than result in re-formation of NO2
via reaction with NO or photolysis. The fraction, f, of NO3 that will
react with organic trace gases is given by

(4)f=kOTGkOTG+JNO3+NOk2.

Figure 12 illustrates the time series (upper plot) and the campaign averaged
diel cycle (lower plot) for f which varies between ≈ 0.1 and 0.4
at the peak of the actinic flux, the variation is largely caused by day-to-day
variability in insolation. As the spectral radiometer was located at a height of 35 m, JNO3 will be slightly overestimated around midday as
light levels within the canopy are lower. The overestimation will be
magnified during the early morning and late afternoon when the forest is in
shade at lower levels but the spectral radiometer is not. The daytime values
for f are thus lower limits. With typical daytime NO levels of
50–100 pptv, the term [NO]k2 contributes ≈ 0.03–0.06 s−1 to NO3 loss, whereas JNO3 has
maxima of close to 0.1 s−1 each day. For comparison daytime values of
kOTG of ≈ 0.05 s−1 were often observed (Fig. 2).

The diel cycle for f shows that even at the peak of the actinic flux, on
average circa 20 % of the NO3 formed will react with an organic
trace gas rather than be photolysed or react with NO in this environment.
This implies that, in the summer–autumn boreal forest, NO3 reactions
may represent a significant loss of NOx not only during the nighttime but
over the full diel cycle, with a significant enhancement in the daytime
production of alkyl nitrates, generally assumed to proceed only via reactions
of organic peroxy radicals with NO.

The first direct measurements of NO3 reactivity to organic trace
gases (kOTG) in the boreal forest indicate that NO3 is
very short lived in this environment with lifetimes generally less than
10 s, mainly due to reaction with monoterpenes. The highest NO3
reactivities were encountered during nights with strong temperature
inversions and a relative humidity of 100 %, and were accompanied by rapid
O3 depletion, together highlighting the important role of nocturnal
boundary layer dynamics in controlling canopy-level NO3 reactivity.
The daytime reactivity was sufficiently large that reactions of NO3
with organic trace gases could compete with photolysis and the reaction with NO,
so that NO3-induced losses of NOx and the formation of organic
nitrates was significant. Measurements of the vertical profile in NO3
reactivity indicate a strong gradient during nighttime, with the highest
reactivity observed below canopy height, highlighting a potential role for
emissions of reactive trace gases from the forest floor. The hydrocarbons
measured did not fully account for the observed NO3 reactivity,
indicating the presence of unsaturated organic trace gases that were not
identified, sesquiterpenes being potential candidates.

Using a newly developed experimental setup, we have made the first direct measurements (during autumn 2016) of NO3 reactivity in the Finnish boreal forest. The NO3 reactivity was generally very high (maximum value of 0.94/s) so that daytime reaction with organics was a substantial fraction of the NO3 loss. Observations of biogenic hydrocarbons (BVOCs) suggested a dominant role for monoterpenes in determining the NO3 reactivity, which displayed a strong vertical gradient between 8.5 and 25 m.

Using a newly developed experimental setup, we have made the first direct measurements (during...